




use "${pathdata_robustness}/RobustnessExperiment5.dta", clear


* Combined Recall, i.e. remember valence AND correct recall (Y) story type (X)



	collapse (mean) combined_recall (seb) seb = combined_recall, by(treatment)

	gen h = combined_recall + seb
	gen l = combined_recall - seb

	tw (scatter combined_recall treatment if treatment == 1, mcolor(red*1.5) ) ///
	(rcap h l treatment if treatment == 1, lw(medthick) lcolor(red*1.5)) ///
		(scatter combined_recall treatment if treatment == 2, mcolor(black*1.5) ) ///
	(rcap h l treatment if treatment == 2, lw(medthick) lcolor(black*1.5)) ///
		 (scatter combined_recall treatment if treatment == 3, mcolor(red*1.0) ) ///
	(rcap h l treatment if treatment == 3, lw(medthick) lcolor(red*1.0)) ///
		(scatter combined_recall treatment if treatment == 4, mcolor(black*0.5) ) ///
	(rcap h l treatment if treatment == 4, lw(medthick) lcolor(black*0.5)), ///
	graphregion(color(white)) ysc(r(0 0.8)) ylab(0(0.2)0.8, angle(horizontal) tlc(none)  glcolor(gs15) glwidth(thin))  ysc(lcolor(none))  xsc(r(0.3 4.7) lcolor(none)) ///
	 xlab(1 "Baseline" 2 "StatPrompt" 3 "NoStory" 4 "NoStoryPrompt" ,valuelabel) xtitle("{bf: Condition}") ytitle("Mean Rate  {c 177} SEM", color(black))  leg(off) ///
			xline(2.5, lwidth(thin) lcolor(black) lp(dash)) ///
	 		yline(0, lcolor(gs10) lwidth(thin)) ///]
	 	title("Correct recall by prompting type",  color(black)) ysize(5) xsize(10) 
	graph export "${pathout_robustness}/figures/figureA8.pdf", replace
